Computer Science: Fully Funded EPSRC DTP PHD Scholarship: Visualisation of Temporal Networks Through Interactions with the Space-Time Cube
Dynamic data sets where each element of the data has its own individual timestamp has become more prevalent. Algorithms for drawing temporal networks within the space-time cube (2D + t) have been devised to allow dynamic graphs to be visualised in an event-based way. However, three-dimensional representations of non-spatial information are difficult to navigate. Therefore, interactive systems are necessary to fully understand the graph structure and how it evolves over time.
The student will investigate perceptually effective ways for dividing and visualising the space-time cube. The project will start by visualising the contents of this space-time cube with an embedded network drawn with an event-based dynamic graph drawing algorithm. The visualisation methods in this case will focus on visualising the already present structure within the drawing which takes into account both spatial position and time simultaneously. Then, we will explore methods that are able to draw the dynamic graph on demand in the space time cube steered by the user.
Eligibility
Candidates must normally hold an undergraduate degree at 2.1 level in Computer Science, Mathematics or a closely related discipline, or an appropriate master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University).
Psychology: Fully Funded UKRI PHD Scholarship: TRUE: Trust in User-generated evidence
Psychology: Fully Funded UKRI PHD Scholarship: TRUE: Trust in User-generated evidence
TRUE is a five-year research project originally selected for funding by the European Research Council (Starting Grant no. 101040463), which will now be funded by a UKRI Frontier Research guarantee grant, in light of the UK’s non-association to the Horizon Europe programme. Through an innovative interdisciplinary methodology combining legal analysis of trials, large online experiments, and mock jury trials, TRUE will develop the first systematic account of trust in user-generated evidence (such as photos and videos recorded by witnesses on their mobile phones), in the specific context of its use in human rights accountability processes.
We are seeking to appoint a PhD student to collaborate on one of the key strands of this project, which will focus on investigating how laypeople make judgments about the trustworthiness of user-generated evidence, and what properties of the evidence (e.g. credibility, relevance) and of the evidence evaluator (e.g. social, motivational, and personality factors) influence these judgments. TRUE’s post-doctoral researcher (Dr Alice Liefgreen) will play a lead role in this strand of the project, though there will also be considerable scope for the successful candidate to shape their own research agenda within the parameters of the broader project and its research objectives.
Throughout the TRUE project, we seek to answer a range of pressing research questions, including but not limited to: (i) do people mistrust user-generated evidence, and why/why not?; (ii) what features of the evidence and/or the individual assessing it influence these judgments?; (iii) how does the evidentiary weight placed on this type of evidence compare to other forms of evidence (e.g. a witness account; DNA evidence)?; (iv) how well-equipped are people to spot deepfakes, and how does this knowledge mediate their perceptions of user-generated evidence?; (v) how likely are people to believe that a real piece of content is a deepfake, and what factors feed into that assessment?; (vi) what are people’s pre-existing knowledge and concern levels about deepfakes, and does that impact on their assessment of user-generated evidence?, and (vii) what are people’s pre-existing levels of trust in media generally, and does that impact on their assessment of user-generated evidence?
We invite interested individuals with a 2.1 level undergraduate degree and master’s degree in Psychology or a closely aligned discipline (e.g., Social and Behavioural Sciences) to apply for this fully-funded PhD position. Candidates should have strong quantitative research skills, to include designing, conducting, and analysing data from experiments.
Candidates should include a 500-word research proposal, setting out a sample research question (within the scope of the TRUE project) and the methods they would use to answer this research question; this should also include a brief description of the analytic approach that would be used to analyse the data.
Eligibility
Candidates must normally hold an undergraduate degree at 2.1 level and a master’s degree. Alternatively, applicants with a UK first class honours degree (or Non-UK equivalent as defined by Swansea University) not holding a master’s degree, will be considered on an individual basis.
English Language requirements: If applicable – IELTS 6.5 overall (with no individual component below 6.5) or Swansea recognised equivalent.
This scholarship is open to candidates of any nationality.
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